Scalable multi-precision simulation of spiking neural networks on GPU with OpenCL

Biologically-realistic multi-precision spiking neural network (SNN) simulation is designed and implemented on a new GPU device Radeon™ HD 7970 using OpenCL framework. The implementation aims to investigate the role of time precision in simulated SNNs. Simulation methods and GPU platforms are reviewed. Simulation model and process are presented and analyzed. The GPU model is capable of simulating a SNN with up to two million neurons. GPU and CPU results are directly verified and found to match exactly.